Smart Health Care Monitoring System based on Internet of Things (IOT)

Shalini, V. Baby

doi:10.1109/icais50930.2021.9396019

Cited by 22 publications

(6 citation statements)

References 11 publications

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“…Similarly, a review of IoT-based health monitoring systems, characterized by the integration of Raspberry Pi, LPC2129, and wearable biomedical devices [46], delves into IoT-driven health monitoring approaches employing the mentioned components. In [47], the authors propose a system for the measurement of body temperature and heart rate. Notably, across these various studies, heart rate and body temperature emerge as consistent focal points.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Active Antennas for IoT-Based Healthcare Monitoring System

Musa,

Shah,

Majid

et al. 2024

IEEE Access

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This work presents the design and implementation of active antennas as a part of a healthcare monitoring system that is based on the Internet of Things (IoT). The monitoring system comprises a SEN11547 pulse sensor and an LM35 temperature sensor for measuring heart rate in Beats Per Minute (BPM) and body temperature in Degree Celsius (°C). This data is then sent to the ThingSpeak IoT platform, which necessitates the integration with the NodeMCU ESP-32S Wi-Fi module to ensure the availability of data. Two dual-band (2.4 GHz and 5.8 GHz) microstrip patch antennas, one with a PIN diode and one without, are fabricated using Rogers Duroid RO3003™ substrate. Both antennas have dimensions of 41 × 44 mm². In order to achieve a dual-band operation at 2.4 GHz, a slot in the shape of an inverted letter U is introduced, to the existing patch which generates a 5.8 GHz frequency band. By controlling the PIN diode's ON and OFF state, the active antenna can switch between a single band of 5.8 GHz and a dual-band of 2.4 GHz and 5.8 GHz. At both frequencies, the measured radiation patterns exhibit bidirectional and directional characteristics in the E-plane, whereas an omnidirectional pattern can be observed in the H-plane. In terms of nonlinear characteristics of the antenna, the third-order intermodulation distortion products (IMD3) frequencies are generated within an input power range of 0 to 20 dBm from the two-tone nonlinear measurements. Specifically, the IMD3 at 2.4 GHz is measured at -36.18 dBm and -47.19 dBm at 5.8 GHz. Additionally, the measurement showed that the 1-dB gain compression point (P1-dB) was not detected at 2.4 GHz, indicating linear behavior within the RF input power range. However, at 5.8 GHz, the P1-dB was observed at an RF input power level of 13.8 dBm, suggesting linear functionality up to this power level. The experimental data are obtained from ten participants with ages ranging between 18 and 40 years old for 10-minutes duration with a 1-minute step size which implies 10 samples. For comparison and validation, the measurements are compared with the commercially available Laird Connectivity 2.4GHz/5.8GHz dipole antenna. It can be observed that the heart rate ranges from 85 BPM to 92 BPM for the active antenna whereas for the reference antenna, the values range from 84 to 90 BPM, which implies a good agreement. On the other hand, the body temperature ranges from 29 to 37°C for the active antenna and from 30 to 36°C for the reference antenna, which infers a good agreement as well. Therefore, it is shown that the proposed dual-band active antennas in this work can be effectively integrated into the IoT-based healthcare monitoring system.INDEX TERMS IoT platform, healthcare monitoring, patch antenna, PIN diode, vital sign, sensor

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Section: Introductionmentioning

confidence: 99%

Design and Implementation of Active Antennas for IoT-Based Healthcare Monitoring System

Musa,

Shah,

Majid

et al. 2024

IEEE Access

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“…The data was processed in real-time using LabVIEW. Some researchers also tried to use and repurpose these systems to measure vital parameters in other similar research [7]- [13]. Previous research relied on designing systems using Arduino and some sensors to measure vital parameters.…”

Section: Introductionmentioning

confidence: 99%

New methodology to detect the effects of emotions on different biometrics in real time

Elgawad

Youssef²,

Nasser

2023

IJECE

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<span lang="EN-US">Recently, some problems have appeared among medical workers during the diagnosis of some diseases due to human errors or the lack of sufficient information for the diagnosis. In medical diagnosis, doctors always resort to separating human emotions and their impact on vital parameters. In this paper, a methodology is presented to measure vital parameters more accurately while studying the effect of different human emotions on vital signs. Two designs were implemented based on the microcontroller and National Instruments (NI) myRIO. Measurements of four different vital parameters are measured and recorded in real time. At the same time, the effects of different emotions on those vital parameters are recorded and stored for use in analysis and early diagnosis. The results proved that the proposed methodology can contribute to the prediction and diagnosis of the initial symptoms of some diseases such as the seventh nerve and Parkinson’s disease. The two proposed designs are compared with the reference device (beurer) results. The design using NI myRIO achieved more accurate results and a response time of 1.4 seconds for real-time measurements compared to its counterpart based on microcontrollers, which qualifies it to work in intensive care units.</span>

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“…In order to give an in-depth examination of its transformational impact on healthcare, this article looks into the design, implementation, and performance evaluation of such a system. An [1] ageing population, an increase in the prevalence of chronic diseases, and a rise in the demand for more readily available and reasonably priced healthcare services are all contributing to a substantial paradigm change in the healthcare industry. Such systems may change the emphasis from reactive therapy to preventative care and early intervention, enhancing healthcare outcomes and lowering costs.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Health Monitoring System: Design, Implementation, and Performance Evaluation

Ghazaly,

Jain

2023

RJCSE

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The Internet of Things (IoT) technology's rapid improvements have opened the door for creative solutions across a range of industries, including healthcare. An IoT-based health monitoring system that aims to revolutionise patient care and healthcare administration is described in this study along with its design, implementation, and performance evaluation. To continuously gather and send health-related data, our system makes use of a network of wearable sensors and gadgets that are seamlessly incorporated into a patient's daily life. Vital indicators like heart rate, blood pressure, temperature, and activity levels are tracked by these devices. To enable real-time analysis and storage, the data is safely sent to a centralised server. Both patients and healthcare professionals can access this information through a user-friendly smartphone application, enabling proactive healthcare decision-making. An effective and scalable architecture is used in the implementation of this system to guarantee the confidentiality, accuracy, and reliability of the data. The data is analysed using machine learning algorithms, which enables the early identification of abnormalities and trends that could portend serious health problems. The system can also produce warnings and notifications, ensuring prompt intervention when it's necessary. Our IoT-based health monitoring system's performance review indicates how well it performs in terms of enhancing healthcare outcomes. The solution gives healthcare professionals immediate access to crucial health information, allowing them to personalise treatment regimens, offer remote consultations, and make educated judgements. Continuous monitoring benefits patients by allowing for early intervention, fewer hospital stays, and an improvement in general health. Additionally, the system's scalability and versatility make it appropriate for a variety of healthcare settings, including small-scale home care and extensive hospital networks.

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Smart Health Care Monitoring System based on Internet of Things (IOT)

Cited by 22 publications

References 11 publications

Design and Implementation of Active Antennas for IoT-Based Healthcare Monitoring System

Design and Implementation of Active Antennas for IoT-Based Healthcare Monitoring System

New methodology to detect the effects of emotions on different biometrics in real time

IoT-Based Health Monitoring System: Design, Implementation, and Performance Evaluation

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